TMG Correlation.

Save weeks or months of work. Correlate thermal models to test data or analysis data efficiently, quickly, and easily

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Build confidence, save time, and innovate faster

Discover a unique approach to thermal correlation that decouples solution time from the number of parameters.

You no longer need to restrict yourself to a reduced set of parameters in an effort to minimize computation time.

TMG Correlation’s powerful adjoint state method lets you match as many thermal model parameters as needed to test data or analysis data – without worrying about computational time.

Even the most complex thermal calibration problems are quick and easy to solve with TMG Correlation – and no other solution uses this approach to correlate thermal models to reference data.

TMG Correlation models
A graph showing how TMG Correlation can handle design variables

How many design variables is too many?

If your usual thermal correlation approach can’t handle your most complex thermal models, how can you get the results you need?

With TMG correlation you can process hundreds of input and output variables at a marginal cost.

Steady-state or transient? Not a problem.

Does the optimal solution for your transient mission problem seem out of reach?

Achieve the near impossible with your thermal analysis.

Minimize data-matching errors, even over many locations or during long transient missions, such as simulations of spacecraft orbiting Earth or turbomachinery operating throughout an aircraft’s flight.

Use your simulation model with a high level of confidence to: 

  • Accurately represent the thermal behavior of the system in all predictable operating conditions
  • Verify that the design meets performance requirements
Steady state vs transient TMG Correlation
TMG Correlation supports hundreds of sensors at a minimal cost

“GOES-S Satellite in Thermal Vacuum Testing” by Dusty Volkel is licensed under CC BY-ND 2.0.

Hundreds of sensors, minimal cost

Complex mission cycles do not need to be a barrier to quickly creating accurate thermal models.

Whether you have two time points or two hundred, TMG Correlation calibrates your model just as fast.

Unleash the ability to handle an unlimited number of sensors.

Gain the flexibility to match your thermal models to temperatures at many different locations without increasing the computational cost.

Various input variables to meet your objectives

Uncertain parameters can lead to uncertain results, questionable accuracy, and extensive experimentation.

With TMG Correlation, you can reduce the uncertainty and the need for approximate-value input parameters:

  • Thermal contact resistance at bolted or glued joints and other contact locations
  • Insulation thermal resistance or degradation
  • Heat transfer coefficients
  • Mass flow
  • Environmental conditions

Easily transform your parameters into design variables that can be modified downstream to converge to a set of known temperatures at multiple sensor locations. 

TMG Correlation features various input variables to meet your objectives
TMG Correlation's intuitive workflow

Intuitive workflow, integrated with Simcenter 3D

Eliminate the tedium of parametrizing your correlation analysis.

TMG Correlation’s simple and concise UI helps you quickly:

  • Import test or simulation data
  • Pair sensor data with existing temperature calculation points (nodes or elements)
  • Review and filter responses for easy verification
  • Define and activate design variables
  • Assign weight factors to temperature targets for particular calibration runs
  • Review results and quickly update and save your calibrated digital twins into your design environment

Unprecedented speed for complex thermal optimizations

Experience a dramatically accelerated model calibration process.

Get calibrated solutions two to three orders of magnitude faster than with traditional DOEs.

With TMG Correlation, calibration times range from seconds to days, based on the type of solution and the size and complexity of the model. 

A graph showing how TMG Correlation can handle design variables

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